Hierarchical Experience Notation for Service Modeling
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Solution Overview
Problem
Current service modeling tools lack structure and fail to provide a quantitative framework for evaluating user or customer experience, as they focus on service delivery rather than explicitly documenting the experience itself, and lack a common non-textual language for documenting sequences of user or customer experience.
Innovation Solution
A system using a classifier based on a hierarchical model of human needs to classify experience states, generating non-textual time series representations of user experiences, which can be analyzed to produce reports and recommendations for improving satisfaction, utilizing a combination of brain science, service sciences, and mathematical analytics to create a coherent analysis framework.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional service modeling tools are used, then service delivery can be documented, but user experience cannot be explicitly documented
Solution Approach 1:
The patent introduces an experience notation as an intermediary layer between service delivery modeling and user experience documentation. This notation acts as a mediator that translates service delivery elements into experience-related attributes, enabling experience documentation without requiring complete redesign of existing service models.
Solution Approach 2:
The experience notation is nested within the existing service model structure. Experience attributes are embedded as additional layers on top of service delivery elements, allowing experience documentation to coexist with and be integrated into traditional service modeling without replacing the entire framework.
2Measurement precision
If questionnaires are used to analyze user experience, then qualitative measures can be obtained, but quantitative framework is lacking
Solution Approach 1:
The patent transforms subjective experience attributes into quantifiable parameters by defining specific experience attributes with measurable properties. This allows qualitative experience data to be converted into quantitative metrics that can be analyzed mathematically while maintaining the essence of user experience.
Solution Approach 2:
The experience notation divides user experience into discrete, measurable attributes that can be individually analyzed. By segmenting experience into specific dimensions, the system enables precise measurement of different aspects of user experience separately, then combines them for comprehensive analysis.
3Adaptability or versatility
If mind-maps and service blueprinting are used, then experience development can be supported, but structure and quantitative evaluation are insufficient
Solution Approach 1:
The experience notation is designed to be universally applicable across different service types and modeling approaches. It can be applied to mind-maps, service blueprints, and other modeling tools, providing a unified framework that enhances their functionality without being limited to a specific modeling methodology.
Solution Approach 2:
The patent replaces informal, qualitative assessment methods with a formalized notation system that enables mathematical and computational analysis. This substitution transforms experience evaluation from a manual, subjective process into a systematic, quantifiable framework suitable for automated analysis.
Data Source
AI summary
A system for describing and analyzing service-related human experience in organizational or commercial environments based on a hierarchical model of needs (e.g. Maslow's hierarchy of needs) is provided herein. The system may include a classifier configured to classify experience states based on a predefined hierarchical model of needs, to yield a classification; a modeler configured to model a real-life environment into a model that includes a set of process instances associated with users; and an experience notation generator configured to: extract experience-related data associated with the users from the model, based on the classification; and represent the experience-related data of each one of the process instance as a non-textual time series, based on the classification. Optionally, the time series may be used to produce reports using an analyzer. The reports may be applied to a remedy engine to generate recommendations for improving the human experience.