Originally published on Designit.
Our modern-day civilisation is built on a trust model that has enabled us to scale from small communities to our current societies by putting our trust into larger institutions. For some time now, this paradigm has become unstable, giving way to the increasing erosion of trust as we know it. What does this mean for businesses and societal institutions? How can trust become something we design for?
In our work as service designers, we bridge private and public institutions, the people they serve, and their mutual goals. While trust plays an important role in this process, it can feel elusive and intangible. We set out to bring this topic down to earth and create actionable tools that we can use strategically as researchers, designers, and technologists.
But of course, before bringing things down to Earth, we had to take a bird’s-eye view!
What does ‘trust’ mean?
Trust is subtle, dynamic, and deep-rooted in its make-up. Although cultural constructs and biases make trust nuanced on many levels, it’s common to talk about trust in an absolute or binary way — ‘I trust you’, ‘I don’t trust you’ or ‘I’ll never trust you again’.
In order to work with trust as designers, we need to understand the elements of trust. A slight tweak of Rachel Botsman’s breakdown of trust concepts is best-suited to our purposes. Botsman’s view considers trust to be built on our perception of four traits: competence, reliability, integrity, and empathy. In our case, we used benevolence instead of empathy, since the latter seemed unnatural for test participants to relate to institutions, organisations, or business entities.
The propensity to trust and perception of risk are unique to each individual. There are many factors that influence a person’s decision-making — just because one signs up for a service doesn’t equate to them trusting it. We started thinking about action versus inaction around what we dubbed the confidence threshold.
While it isn’t a perfectly straight line, the confidence threshold illustrates the relationship between confidence, trust, and transparency. ‘Trust’ and ‘transparency’ are often used interchangeably because they can strive for the same thing: confidence.
Trust is time-sensitive and influenced by a whole slew of other factors – risk perception, trust propensity, and individual motivations – and the weight given to competence, reliability, integrity, and benevolence as individuals.
Bringing it back to design, here are a few ways to give trust a boost.
Although transparency doesn’t equate to trust, it can act as a catalyst for trust. Transparency helps to build a track record over time, and the very intention to be transparent can be related to benevolence and integrity.
At the moment, transparency is in high demand because there are low levels of trust across society. Over time, if transparency is used to build trustworthiness, transparency will become less relevant for people who develop trust.
Another mechanism for building trust — especially interesting when designing within an ecosystem — is trust transferral. This is where aspects of capability or character are ‘transferred’ to another entity.
For example, an entity might choose to partner with another organisation to leverage their reputation that has already been built up over time, say partnering with Volvo to reinforce capability in safety.
Or you might introduce a figure of authority to oversee or validate certain claims. Authority doesn’t always need to be a top-down model, such as governments or police forces, it could be an authority on a particular subject matter or a set of values that the entity subscribes to by choice. For example, B corporations that contribute to character.
These days, another form of transferral can be seen frequently in platform-facilitated trust models. Peer reviews and ratings contribute to the making or breaking of the trustworthiness of another party’s claim, such as Airbnb.
Before strategically enacting any of these trust mechanisms, we first need to be able to get a view of where and why, competence, reliability, integrity, or benevolence is either being supported or falling short in a particular relationship.
Trustability framework: A work in progress for designing trustworthiness
During our exploration of trust, we decided to focus on creating a framework to help uncover opportunities that address trust gaps. The framework works in combination with familiar design practices but invites people to work with specific tools to guide the conversation and ideate ways of creating the foundations for trust. The tools — a map and set of trigger cards — contain the key concepts we think will help designers incorporate trust into their crafting. This is still a work in progress, so we’d love to hear your feedback.
Recently, we brought this trust exploration to life during a project for Food Agility CRC. The ag-tech industry is an evolving space in which, because of its complex ecosystem, there is a need to develop greater trust between actors. During the project, we undertook research across the organisation’s partner ecosystem to map the relationships across four actors groups: producers and processors, technology companies, researchers, and the client themselves, Food Agility CRC. In this ecosystem, partners come together to create and commercialise new data solutions for the benefit of the Australian agri-food industry, leveraging Australia’s world-class research capability.
We’re going to go through the steps of the trustability framework, which are found along the top of the map, and share examples based on the relationship between producers and technology companies.
Trustability Framework Steps
While steps 1 & 2 can be carried out before using the actual tool, it’s useful to keep steps 3 to 7 in mind so that project content can feed into the trust concepts.
1. ACTORS’ EXCHANGE MAP
Sketch a high-level actors map showing what is being exchanged between key actors (e.g value, goods, services, information).
During the project, we created a map to understand the relationship and value exchange among actors. This is a simplified version zoomed into the relationship between producers and technology companies in the context of a Food Agility project.
In summary, producers get access to potential data solutions that enhance their decision-making and performance, while technology companies get access to real customer data to develop and commercialise new offerings.
2. FACT-FINDING COLLATION
Based on research, gather the known facts about key actors’ behaviours, needs, emotions, and contextual circumstances. Analysing our research results, we identified a set of behaviours and needs that were affecting the relationship between actors. This data helped us build a picture of each actor’s realities and perceptions. For example:
- Producers’ business models are tightly related to the environment and the livelihood of their communities — they are really cautious about who they share their IP and data with.
- Technology companies struggle to demonstrate the value of data to encourage producers to share theirs with them.
- Producers are not familiar with the technical aspects of data management and security.
- Technology companies need their customers to provide reliable and high-quality data for them to deliver full value through their offering.
Steps 3, 4 & 5 have a dedicated space on the map. They are designed to help break down research inputs in a way that’s more useful for explicitly working with trust.
3. POCKET PROFILE
Trust is about leaping into the unknown with confidence — regarding the exchange, clarify each actor profile’s primary motive and unknowns. In Food Agility’s collaborations, the level of uncertainty around the outcomes is pretty high in the early stages. Each actor faces their own specific set of risks and potential gains. Based on our research, we completed the producer’s pocket profile as follows:
- Which actor profile will this map represent? Producers who are considering a data-sharing collaboration with other Food Agility partners.
- What is the main reason for engaging with other actors? Build the capability to leverage their data for enhanced decision-making, productivity, and business performance.
- What are the main issues, fears, concerns, or risks that the actor is not certain of? Producers find it hard to grasp the potential value and risks of sharing their data with partners, and they are particularly unsure if the commercialisation of the final outcome will compromise their competitive advantage.
4. TRUSTWORTHINESS TRAIT IDEALS
Trust is built on our perception of four traits: competence, reliability, integrity, and benevolence. Complete the sentence in each quadrant to define this actor profile’s ideals for how someone trustworthy in each trait would act. Informed by our research, this is a glimpse of how we defined the trust ideals for producers:
- BENEVOLENCE: I believe that technology partners are benevolent if… they prioritise the sustainability of my business, my community, and the environment over profits.
- INTEGRITY: I believe that technology partners have integrity if… they honour the partnership and hold back from offering a product or service that can threaten my competitive advantage.
- COMPETENCE: I believe that technology partners are competent if… they are able to develop a viable data solution for my business that enhances my performance and increases my profits.
- RELIABILITY: I believe that technology partners are reliable if… they are able to contain and manage IP and data breaches during and after the project.
5. TRUSTWORTHINESS PERCEPTION
Our perception of others is built on their actions, our biases, and other sources that inform our views. Regarding each trait ideal, detail the forces that currently inform this actor profile’s perception — for good or for bad.
During our research, we found that the differences between industries and business models led to several misalignments between producers and technology partners, creating tensions in the relationship that affect how comfortable producers feel trusting technology partners. Here are some examples from our research of how the producer profile’s trust ideals are either met or not met when it comes to technology companies.
Ideal: I believe that technology partners are benevolent if… they prioritise the sustainability of my business, my community, and the environment over profits.
Perception: Producers perceive that many technology companies are interested in short-term partnerships and returns, and not in developing solutions for producers’ long-term business sustainability.
Ideal: I believe that technology partners have integrity if… they honour the partnership and hold back from offering a product or service that can threaten my competitive advantage.
Perception: Producers perceive that some technology companies develop products, leveraging producers’ data and resources, to service direct competitors with little consideration for the integrity of their partner’s competitive advantage.
Ideal: I believe that technology partners are competent if… they are able to develop a viable data solution for my business that enhances my performance and increases my profits.
Perception: Producers perceive that some technology companies can’t guarantee that projects will result in the development of data solutions for producers — the business case may not be viable for them to develop the product.
Ideal: I believe that technology partners are reliable if… they are able to contain and manage IP and data breaches during and after the project.
Perception: Producers perceive that data security is technology companies’ area of expertise and they feel comfortable with them taking care of the cybersecurity measures.
Steps 6 & 7 happen over the information filled in the map. They require analysis and ideation skills to determine the best areas and ways to develop trustworthiness.
6. TRUST GAPS & OPPORTUNITIES
Analyse the ideal traits and the actor profiles’ corresponding perceptions. Prioritise which trust gaps should be addressed and which trust-building opportunities should be leveraged.
One of the key trust gaps that producers experience with technology companies is around the perception of character. Producers don’t tend to have confidence in tech companies’ integrity, so they feel that they risk compromising their own competitive advantage by releasing sensitive data to tech partners. This is proven an important trust gap to address, as it creates a bottleneck for the entire ecosystem.
7. TRUST TRIGGER IDEATION
Use the Trust Trigger Cards to help ideate new trust mechanisms for the gaps and opportunities. After a process of ideation and conceptualisation, one of the key opportunities we worked with leveraged the trust mechanism of interdependence — how might we increase confidence by sharing benefits and losses across actors?
We defined an initiative to help our client facilitate agreement models that make risks, benefits, and losses more interdependent among partners, allowing producers to feel more confident in data-sharing partnerships.
In the digital world we live in today, where autonomous cars are hitting the road, experiments with synthetic reality alter our perception, and the use of data and AI propagates even further in a growing digital population, the question of trust will be an increasingly crucial aspect of the way we design at any level.
We hope you find some inspiration in this exploration, something that might help you bring designing for trustworthiness closer to your daily practice. We would love to hear your feedback about the framework. Perhaps you see a way to simplify it further, apply the concepts in different ways, different examples for the trigger cards, or whatever thoughts cross your mind. We’re all ears!
Download the Trustability Framework — Trust Map and Trust Triggers. If you have feedback, please let us know through this link.