Decision Making, Dashboard Displays, and Human Performance in Service Systems

Decision Making, Dashboard Displays, and Human Performance in Service Systems

Megan L. Moundalexis (Applied Physics Laboratory, Johns Hopkins University, Laurel, MD, USA) and Barin N. Nag (Department of E-Business & Technology Management, College of Business & Economics, Towson University, Towson, MD, USA)
DOI: 10.4018/ijisss.2013100103
OnDemand PDF Download:
No Current Special Offers


Service systems are often characterized by large components of human work and the need to make decisions based on human performance. Human cognitive limitations and the abilities of computers to compensate led to decision support systems (DSS). While a computerized DSS fits the needs of human cognitive limits, the strengths of human cognitive abilities are often overlooked. Human performance is often monitored by task completion in terms of timeliness and accuracy. A failure of this is that cognitive feedback is generally not given to the operator until after the task. Dashboard displays that are already widely used in manufacturing and other operational applications give current performance information and can take advantage of human cognitive capabilities. This paper presents the concept of decision support in human performance by exploring the extension of the dashboard display concept to human performance monitoring as a cognitive feedback mechanism. Examples specific to the service sector are provided in the context of a Help Desk environment.
Article Preview


Humans are cognitively at a disadvantage compared to computers in some respects. It is documented in Bui and Loebbecke (1996); Turban, Sharda, & Delen (2011); Zachary (1986); and in other research, that humans are more limited in terms of processing and storage than computers. For example, a human’s slower speed of information retrieval is just one cognitive limitation. An individual’s problem solving capability may also be more restrictive than a computer. Other mental restrictions which affect human decision performance as stated by Zachary (1986), include a difficulty in the performance of quantitative operations, unreliability in recall of information, and biases in inference processes that are predictable. The paper also describes that in order to make a decision, the decision maker needs information and that must be constructed by accessing data via sensory channels, and interpreting this data by accessing knowledge via long-term memory. As a result of human limitations, computers became useful tools for helping humans make better decisions as seen in Landvater (1997).

Decision Support Systems (DSS) were developed to overcome cognitive limits by taking advantage of computer capabilities. It is stated in Holsapple, Jacob, and Winston (1994) that an ideal decision support environment is an extension of the user’s private cognitive world. It enhances cognition by pushing back cognitive limits on knowledge representation. The knowledge processing capabilities augment the user’s mental skills, and overcome cognitive limits on the speed and capacity of human knowledge processing. It is noted in Zachary (1986) that computer support may be necessary when a cognitive task is difficult for a decision maker to perform despite having an appropriate representation and strategy. DSS evolved as a means to surpass some limits of human cognition. The application of a DSS has a number of positive effects on decision making. As stated in Zahir (2002), a DSS manages information overload and removes the information immediacy effect where a human decision maker in an information overload situation relies most heavily on the most recent piece of information. A DSS increases the time efficiency of decision making and also makes the decision more rational and consistent over time. One type of DSS is a Dashboard display, as described later in more detail, designed to describe and report current status or performance level.

DSS and Dashboard systems are used extensively worldwide today to monitor performance in industries and operations where work increments are quantifiable. Typically these are manufacturing and logistics operations where material modification and movement are involved, and serve as markers for performance increments in the dimensions of time, cost, and quality. In these industries, human involvement and performance is often represented as the surrogate of material changes.

A service process is defined as any non-manufacturing operation or activity in a manufacturing or non-manufacturing operation. In a service system, the material surrogate for performance is less dominant and the measurement and monitoring of human performance becomes less quantifiable but more important. The special importance of human performance monitoring in services arises from the nature of the service product that is consumed as it is produced. Human performance monitoring is an aspect of quality management in a product delivery where no quality checks are possible until after the delivery. A characteristic of a service product or system is that many aspects of the process are not well-defined, or do not have quantifiable parameters. This is where one has to resort to indefinable measures of human cognition and psychology. Many of the illustrations and examples provided in this paper are from the Help Desk aspect of the service sector.

Complete Article List

Search this Journal:
Open Access Articles
Volume 14: 4 Issues (2022): 2 Released, 2 Forthcoming
Volume 13: 4 Issues (2021)
Volume 12: 4 Issues (2020)
Volume 11: 4 Issues (2019)
Volume 10: 4 Issues (2018)
Volume 9: 4 Issues (2017)
Volume 8: 4 Issues (2016)
Volume 7: 4 Issues (2015)
Volume 6: 4 Issues (2014)
Volume 5: 4 Issues (2013)
Volume 4: 4 Issues (2012)
Volume 3: 4 Issues (2011)
Volume 2: 4 Issues (2010)
Volume 1: 4 Issues (2009)
View Complete Journal Contents Listing