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Automation is useful to supplement the capacity of services. Self-service channels are increasingly popular among user s now accustomed to human–computer interactions, devices and appliances. The ubiquitous channel of service delivery is the internet with browsers acting as service access points that are widely distributed, standardized and highly familiar through constant use. Advances in artificial intelligence and speech recognition have improved the capabilities of software-based service agents in conducting dialogue with customers. The richness of the dialogue and the complexity of the interaction continue to increase.
The capacity of self-service channels has very low marginal cost, is highly scalable, does not suffer from fatigue, offers highly consistent performance, and is offered on a 24/7 basis at a relatively low cost. Additionally, users perceive the following disadvantages with human-to-human interactions with respect to incident s and problems:
Self-service channels are effective when appropriate knowledge and service logic is embedded into the self-service terminal. Service Design should ensure that Use Case analysis is performed to ensure usability, efficiency and ease in interactions through the automated interface.
Another example would be the use of the productive capacity of customers through self-service channels. Advances in human-computer interaction and the richness of interaction technologies, such as touch-screens, scanners and signature capture devices, allow for certain service activities to be completed without the presence or intervention of service staff.36 This is a very intelligent way to adjust capacity that is highly sensitive to the presence of demand. Each customer brings one additional unit of productive capacity, instantly added and removed from the system without inventory-carrying costs to the service provider.
It is necessary to evaluate the level of control user s are expected to assume with self-service options. The level of control should be commensurate with the proficiency and experience level of the users.12 In almost every population of users there are differences in levels of experience, skills, aptitudes and work environment s that determine preferences for methods and modes of interaction. The attributes and function s of service interfaces should take these differences into account. There will be trade-offs as different segments of users expect to be served according to their preferences. Some prefer step-by-step guidance while others prefer efficiency and flexibility. Advances in artificial intelligences and machine learning are creating a new level of sophistication for service interfaces, which are context-aware, forgiving of new users, and capable of dialogue embedded with inquiry. The principle of forgiveness requires that the design of a service helps users avoid error s. When the errors do occur, the design should minimize negative consequences.
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Types of service technology encounters | | | Technology-mediated service recovery |