Skip to main content

Dynamic Interaction Maps (DIM)

By Tojin T. Eapen

Journey maps can be used to visualize the different stages of a user's experience and track their progress through a process. In order to incorporate dynamic interactions between these stages, it is important to identify the different stages and consider how they may interact with each other. This can be done by creating a matrix of the stages and their potential interactions.

Dynamic Interactions at an Airport

For example, consider the journey of a passenger at an airport, which has three stages: check-in, security, and boarding. The sequence of these stages is fairly similar for most users, but in some contexts, different users may experience different sequences of stages. Once the stages have been identified, it is important to consider the interactions between the stages, as well as the interactions within each stage.

One type of interaction is a same-stage interaction, where an output attribute of a stage changes dynamically based on an attribute within the same stage. For example, in the check-in stage of an airport journey, the number of staff available to assist passengers may increase based on the number of passengers waiting in line to check in. Similarly, in the boarding stage, the boarding time may be advanced or delayed based on immediate information, such as flight status. These self-interactions within the stages can be represented visually to show how they change over time.

Overall, journey maps can be configured to incorporate dynamic interactions between stages in order to more accurately reflect the user's experience and track their progress through a process. By identifying the different stages and considering how they may interact with each other and within themselves, it is possible to create a more detailed and comprehensive journey map that helps to understand and optimize the user's experience.

Between-Stage Interactions

Interactions between stages refer to how inputs from one stage may influence outputs in a later stage, and how inputs from a future stage may influence outputs in an earlier stage. These types of interactions can provide important insights into the user's experience and help to identify any potential bottlenecks or issues that may arise.

For example, if there is a delay in the check-in stage of an airport journey, the airline may start boarding earlier to compensate for the lost time. This is an example of how inputs from one stage (the delay in check-in) can influence outputs in a later stage (the earlier boarding time).

Inputs from Future Stages

In addition to interactions between consecutive stages, it is also possible for inputs from a future stage to influence outputs in an earlier stage. This type of interaction may occur in cyclical or repetitive processes, or when some users in one stage follow other users in a later stage. For example, the outputs of the security stage in an airport journey may inform the check-in stage for future journeys. Similarly, the output of a stage may depend on predicted attributes of a later stage.

Overall, understanding the interactions between stages is important for identifying potential issues and optimizing the user's experience. By considering how inputs from one stage may influence outputs in a later stage, and how inputs from a future stage may influence outputs in an earlier stage, it is possible to create a more comprehensive journey map that helps to understand and improve the user's experience.

Input and Output Attributes in DIMs

In dynamic interaction journey maps, each stage is composed of attributes or variables that relate to the user, the product or service, the provider, or the environment. These attributes, also known as input attributes, may be stable characteristics or varying attributes. Stable characteristics are attributes that do not change, such as a person's age or personality. Varying attributes are attributes that can change, such as a person's mood or body temperature.

Input attributes can provide signals that trigger an output relationship, where the output is dependent on some combination of input attributes. For example, knowledge that there is a delay in an incoming aircraft may be a signal, while the input attributes may be the class of the passenger or the weather conditions.

Output attributes, also known as adapted attributes, are attributes that change based on input or signals from other stages. These output attributes can be related to the user, the product or service, the environment, or the provider. For example, in an airport journey, user expectations may be adapted by providing information, the speed of the service may be adapted based on demand, the temperature of the environment may be adjusted, and the number of staff at a station may be adapted based on the number of passengers.

Overall, understanding the input and output attributes of each stage is important for identifying potential points of interaction and adapting the user's experience in real-time. By considering how information from other stages can be used to adapt immediate or future attributes, it is possible to create a dynamic interaction journey map that helps to understand and optimize the user's experience.

To learn how leading Fortune Global 500 companies such as ABB, Bosch, Google, Samsung, and NetApp have used Innomantra's Functional Innovation Methodology to turbocharge their idea management process, schedule a meeting today at calendly.com/innomantra.

Comments