“Designing is about exploring what is possible tomorrow instead of solving the problems of today. Rather than looking at the world in terms of problems, we feel it is much more productive and challenging to look for possibilities and opportunities to contribute to the lives, dreams, habits, peculiarities and goal of people, whether they have been clearly articulated or not.”

Hekkert, van Dijk, “Vision in Design”

This text is an introduction where I am presenting the framework for a product/service design. The framework allows to create a project space, helps to organize a design work during pre-prototyping (or pre-deliver) steps of a design process, and yields a shared understanding of problem and solution. Being a compilation of multiple approaches and a result of my own experience in designing, the framework requires further study.

Co-evolution of problem and solution

Designing is about exploring an interplay between problem and solution, and this interplay takes the form of “co-evolution of problem-solution” (Dorst, Cross, 2001). “It seems that creative design is not a matter of first fixing the problem and then searching for a satisfactory solution concept. Creative design seems more to be a matter of developing and refining together both the formulation of a problem and ideas for a solution, with constant iteration of analysis, synthesis and evaluation processes between the two notional design ‘spaces’ — problem space and solution space. The model of creative design <…> is based on such a ‘co-evolution’ of the problem space and the solution space in the design process: the problem space and the solution space co-evolve together, with interchange of information between the two spaces.”, as Dorst and Cross (2001) put it. In other words, a designer aims at coupling and considering together the present situation (problem space) and a desired future state (solution space). These two act as communicating vessels and cannot be divided. The more detailed description of the present situation a designer compiles, the more boundary conditions, which frame possible solutions, are being created. And the other way round — often elaboration on a particular solution can illuminate overlooked and essential details of the problem.

Design process

In this text, I’ll be referring to two models which uncover features essential for understanding the nature of a design process:

• The Innovation as a Learning Process (Beckman, Barry, 2007), described as follows: “This problem finding/problem selecting, solution finding/solution selecting, or story-telling process is also a learning cycle that draws upon the four learning styles. An ideal learning cycle is one in which the learner goes through all four phases — experiencing, reflecting, thinking, and acting — in a recursive process that is responsive to the learning situation and what is being learned. Immediate or concrete experiences are the basis for observations and reflections [observation to frameworks]. These reflections are assimilated and distilled into abstract concepts from which new implications for action can be drawn [frameworks to imperatives]. These implications can be actively tested and serve as guides in creating new experiences [imperatives to solutions and back to observation].”

• The Analysis-Synthesis Bridge Model (Dubberly, Evenson, Robinson, 2008), the structure of which is explained as follows: “The left column represents analysis (the problem, current situation, research, constituent needs, context). The right column represents synthesis (the solution, preferred future, concept, proposed response, form). The bottom row represents the concrete world we inhabit or could inhabit. The top row represents abstractions, models of what is or what could be, which we imagine and share with others.”

Being organized in the form of two-by-two matrix, both models reveal the structure and explain the essence of designing. What is significant for me is the iterative interplay between concrete and abstract worlds, as well as between analysis and synthesis activities. The design process appears as four steps formed by intersections between concrete, abstract, analysis, and synthesis realms.

Although being far from linear in real life, the design process can be described — based on models presented — as a sequence of the following steps:

1. Observations or What is. Being grounded into reality, design work begins in the concrete realm. A designer starts with deconstruction and analysis of the present situation in order to describe the reasons that trigger the project as well as a product/service strategy. This step is devoted to research and gathering data about customers & users, their context of use, goals, and needs. The key is to collect as many details as possible in order to articulate circumstances that make the project actual from both customers & users and business perspectives as well as to describe the present situation on different levels — personal, social, country, etc.
2. Frameworks or Model of what is. The design process moves forward from the concrete to abstract realm. A designer proceeds with interpreting research data and transforming it into information and, eventually, into knowledge about the present situation. Through framing, sense making, and reframing a designer gains understanding of the status quo and gets in a position to consider it from different perspectives. The purpose of this step is to come up with a model of the present situation which will be used as a basis for building a model of a desired future during the next step of the process.
3. Imperatives or Model of what could be. During this step, which still takes place in the realm of abstractions, synthesis becomes the primary method of design work. Now that a designer has completed a comprehensive model of what is, they proceed with speculating and brainstorming hypotheses to outline a model of what could be. A designer points out (1) value which is supposed to be delivered to people, (2) interactions with a possible solution whereby this value can be conveyed to people, and, finally, (3) what possible solutions can look like. Eventually, the aim of this step is to describe alternatives that can potentially resolve customers’ & users’ needs and address business goals, in other words, build a model of a desired future.
4. Solution or What could be. The design process returns from abstract realm to concrete one while synthesis remains the primary method of work. As a designer moves from a model of a desired future towards its embodiment, they transform ideas into tangible prototypes. This step is aimed at shaping a number of possible solutions in order to test them and select the most appropriate one. Testing prototypes and selecting a solution connects this step to the Observations step which makes the design process looped and iterative.

The proposed canvas covers pre-prototyping steps of the design process — What is, Model of what is, and Model of what could be.

Models

Co-evolution of problem and solution does not imply that these two are tied directly. Rather, as both figures above demonstrate, the connection between problem and solution is indirect or mediated. Apparently, there exist two intermediate elements or stages of a design process — Model of what is (or Frameworks) and Model of what could be (or Imperatives). As Kolko (2015) points out, “Modeling delineates between problem finding and problem solving, acting as a form of problem understanding.” Although these two models (mentioned earlier) are often can be considered insignificant, they are essential for a designer to gradually move across a design process from present to future, from problem towards solution.

Since the notion of model has been used above, there’s a need to elaborate on this. Although, models are used extensively across scientific disciplines and have a number of manifestations — maps, pictures, diagrams, etc. — there is no “all-encompassing and singular definition of the model” (Hof, 2018). However, from the functional perspective, scientific modeling is used “to represent and increase information. The core purpose for using models is the simplification, visualization, idealization, modification, or hypothetical realization of phenomena together with the aim making the latter easier to understand.” (Hof, 2018) In other words, models are abstractions which reflect one’s understanding or description of the world.

Models are a result of observation, framing, and making sense of reality. Observation implies gathering data that reflects a situation and provides material for further work. To frame a situation means to set up subjective boundaries based on product/service strategy and one’s unique point of view. This way, framing helps to highlight “a few salient features and relations from what would otherwise be an overwhelmingly complex reality.” (Hideaki, 1999) Sense-making is understanding connections and relationships between seemingly unrelated pieces of reality. Together with the subjectiveness, both framing and sense-making depend on the purpose. Observation, framing and sense-making together allow to (1) collect data that outlines and reflects a piece of reality (2) extract subjectively and pragmatically essential aspects of reality as well as (3) understand and describe its structure, in other words, to create models. As a result, “Models [are] neither true nor false but rather strongly applicable or weakly applicable <…> They are determined by a pragmatic criterion, not a truth criterion.” (Mittelstraß, 2005).

Stachowiak (1973) suggests the following features of models:

• Mapping. Model represents an original regardless of its character — natural, artificial, existing, imagined, or even other model.
• Truncation. Model do not consider all aspects of an original, rather, they include only relevant to the model creator or user.
• Pragmatics. Model works as a replacement of an original (1) for certain model users (for whom?), (2) within certain time frame (when?), and (3) restricted to a certain purpose (what for?).

Dubberly (2009) points out two specific aspects of models:

• Observations suggest models. “Models are always models of something”, as Stachowiak (1973) puts it. It means, that the starting point for building a model is observation or gathering data that reflects reality. Once collected, data can be organized — filtered, sorted, grouped, — interpreted, and transformed into a model of a piece of reality.
• Models guide actions. Models are hypotheses made in an attempt to explain reality. They are used as simplified visualization of an original. By reducing the number of the original’s aspects under consideration, models help to recognize similarities between an observable new situation and other, already known, ones; in other words, models help to link the present to one’s past experience. Doing so, models allow to navigate reality by making predictions of likely futures and, eventually, to act.

A model is more than a visualization used instead of an original — cognitive science considers a model to be an “epistemic tool” (Boon, Knuuttila, 2008). As Stachowiak (1973) stated: “All cognition is cognition in models or through models.” Humans create knowledge about the world by forming mental representations in the first place, in other words, by constructing models. Being a fruit of observation, framing and sense making, models allow to extract relevant and essential aspects of reality and to understand relationships between the pieces, in other words, to create knowledge about reality. Also, ‘playing with models’ (1) shows the reality from different perspectives, (2) spotlights overlooked relationships, as well as (3) makes it possible to see problems from different angles and understand them differently to reveal opportunities for improvement.

So, treating models as an epistemic tool, it’s possible to say that “models help bridge the gap between observing and making.” (Dubberly, 2009) Being abstract, models guide a designer from analysis to synthesis and help to understand a present situation as well as imagine alternative futures. Models prepare the ground for reframing a problem in order to reveal the possibilities housed in challenges. Eventually, it is models that “bridge the gap” between problem and solution.

Project space

Co-evolution of problem and solution can be thought of as interplay between “notional design ‘spaces’ — problem space and solution space” (Dorst, Cross, 2001), as it has already been mentioned. However, the connection between problem space and solution space is indirect or mediated. It is models — or models space — that bridge the gap between problem and solution spaces. Designing needs a specific space — project space — which combines problem space, models space, and solution space in order to foster co-evolution of problem and solution.

Project space is a place to accumulate, organize all essential information about the project together with making it visible and accessible. Also, it stimulates collaboration between everyone involved and allows to create a shared understanding of the problem and solution.

Project space can be a physical spot in a room organized for this purpose or a specific digital tool. Anyway, a project space invites team members and stakeholders to contribute. As a result, such space outlines a big picture of the project and serves as a benchmark for design decisions later.

Project space fosters comprehensive understanding rather than fragmented one. What is crucial for this purpose is visualization which is, as Kolko (2015) putsit, “is the act of externalizing ideas.” Visualization makes it possible to manipulate research data, filter it, forge connections between its pieces, and group them into chunks. Doing so, a designer gets in a position to make sense of a present situation and gains all-round understanding of a problem and opportunities.

Kolko (2015) lists a number of essential implications of visualization:

1. Visualization helps to compare. Since the capacity of one’s working memory is limited, relatively larger amount of entities and attributes can be considered, evaluated and compared while being visualized.
2. Visualization reveals changes over time. Once visualized, not only different states are easier to be tracked, but also the changes are easier to be recognized than when being just verbalized.
3. Visualization describes spatial relationships. Visualization helps to organize and shape data in different forms for different subjects so as to reveal spatial relationships, such as scale, proximity, etc.
4. Visualization makes ideas tangible. A visualized idea acquires form and, as a result, can be stored, shared, and critiqued.
5. Visualization fosters creation of new knowledge. Visualization makes it possible to apply different frames, build connections between disparate ideas, and, eventually, understand them differently.

Having everything visualized and collected in one place which is accessible for the whole team, it becomes possible to align shared mental model. “Once externalized, the ideas become ‘real’ — they become something that can be discussed, defined, embraced, or rejected by any number of people, and the ideas become part of a larger process of synthesis.” (Kolko) Project space fosters communication and yields a shared understanding of problem and solution.

So, project space is a specific environment which helps to organize a design work by providing a spot for creation of a big picture of the project, aligning a shared vision, and collaboration between everyone involved.

The canvas structure

To shape a project space, it’s essential to observe the situation — both present and future — from various viewpoints. I suggest a framework in the form of a canvas which consists of a number of blocks. Each block represents a topic to cover prior to representing ideas into tangible prototypes. Having these topics at hand, it’s easier for a designer to come up with (1) appropriate questions to ask while decomposing a problem as well as (2) facets to consider while shaping a solution. Also, there’s a particular spot between a problem and solution for building models of a present situation and desired future. This way, the canvas structures design work and serves to externalize one’s thinking.