Dashboards in performance management: The foundations and research opportunities for their effective use

When designed effectively dashboards are expected to reduce information overload and improve performance management. Hence, interest in dashboards has increased recently,which is also evident from the proliferation of dashboard solution providers in the market. Despite dashboards popularity, little is known about the extent of their effectiveness in organizations. Dashboards draw from multiple disciplines but ultimately use visualization to communicate important information to stakeholders. Thus,a better understanding of visualization can improve the design and use of dashboards. This paper reviews the foundations and roles of dashboards in performance management and proposes a framework for future research, which can enhance dashboard design and perceived usefulness depending on the fit between the features of the dashboard and the characteristics of the users.

[1]  James M. Peters,et al.  Decision making, cognitive science and accounting: An overview of the intersection , 1993 .

[2]  Mark S. Silver,et al.  Decision Support Systems: Directed and Nondirected Change , 1990, Inf. Syst. Res..

[3]  Kevin Mullet,et al.  Designing Visual Interfaces: Communication Oriented Techniques , 1994 .

[4]  J. Moran,et al.  Sensation and perception , 1980 .

[5]  C. Heaps,et al.  Similarity and Features of Natural Textures , 1999 .

[6]  Patrick Moore,et al.  Gestalt Theory and Instructional Design , 1993 .

[7]  Gerald K. Debusk,et al.  Components and relative weights in utilization of dashboard measurement systems like the Balanced Scorecard , 2003 .

[8]  Abel G. Oliva,et al.  Gist of a scene , 2005 .

[9]  Bruce H. Clark,et al.  Dashboards & Marketing: Why, What, How and What Research is Needed? , 2009 .

[10]  Ben Shneiderman,et al.  Readings in information visualization - using vision to think , 1999 .

[11]  E. Ziegel,et al.  The Balanced Scorecard , 1998 .

[12]  Iris Vessey,et al.  Cognitive Fit: A Theory‐Based Analysis of the Graphs Versus Tables Literature* , 1991 .

[13]  Dennis F. Galletta,et al.  Cognitive Fit: An Empirical Study of Information Acquisition , 1991, Inf. Syst. Res..

[14]  S. Fukuda,et al.  Development of man-machine interfaces based on user preferences , 2001, Proceedings of the 2001 IEEE International Conference on Control Applications (CCA'01) (Cat. No.01CH37204).

[15]  Ed O'Donnell,et al.  How information systems influence user decisions: a research framework and literature review , 2000, Int. J. Account. Inf. Syst..

[16]  Boon Wan Tan,et al.  The impact of interface customization on the effect of cognitive style on information system success , 1991 .

[17]  Roy R. Behrens Design in the Visual Arts , 1983 .

[18]  Iris Vessey,et al.  Multiattribute Data Presentation and Human Judgment: A Cognitive Fit Perspective* , 1994 .

[19]  Michael L. Mack,et al.  Identifying the Perceptual Dimensions of Visual Complexity of Scenes , 2004 .

[20]  Joy Teague,et al.  Personality type, career preference and implications for computer science recruitment and teaching , 1998, ACSE '98.

[21]  R. Banker,et al.  The Balanced Scorecard: Judgmental Effects of Performance Measures Linked to Strategy , 2004 .

[22]  Gerardine DeSanctis,et al.  Graphical presentation of accounting data for financial forecasting: An experimental investigation , 1989 .

[23]  Mary A. Malina,et al.  Communicating and Controlling Strategy: An Empirical Study of the Effectiveness of the Balanced Scorecard , 2001 .

[24]  P. Quattrone Books to be practiced: Memory, the power of the visual, and the success of accounting , 2009 .

[25]  Michael L. Roberts,et al.  Financial and nonfinancial performance measures , 2008 .

[26]  Robert H. Chenhall,et al.  THE EFFECT OF COGNITIVE STYLE AND SPONSORSHIP BIAS ON THE TREATMENT OF OPPORTUNITY COSTS IN... , 1991 .

[27]  John R. Anderson,et al.  A Theory of the Origins of Human Knowledge , 1989, Artif. Intell..

[28]  Allen Newell,et al.  Human Problem Solving. , 1973 .

[29]  Ron Weber,et al.  Structured tools and conditional logic: an empirical investigation , 1986, CACM.

[30]  Larry R. Davis,et al.  Report format and the decision maker's task: An experimental investigation , 1989 .

[31]  E. Cardinaels The interplay between cost accounting knowledge and presentation formats in cost-based decision-making , 2008 .

[32]  Peter G. W. Keen,et al.  Decision support systems : an organizational perspective , 1978 .

[33]  Chandler Stolp,et al.  The Visual Display of Quantitative Information , 1983 .

[34]  Matthew J. Liberatore,et al.  The Effects of Display Formats on Information Systems Design , 1989, J. Manag. Inf. Syst..

[35]  Angelina Villarreal,et al.  PERFORMANCE DIFFERENCES IN THE USE OF GRAPHIC AND TABULAR DISPLAYS OF MULTIVARIATE DATA , 1987 .

[36]  Frédéric Adam,et al.  Developing Practical Decision Support Tools Using Dashboards of Information , 2008 .

[37]  Carlos Corona,et al.  Dynamic performance measurement with intangible assets , 2008 .

[38]  Mark S. Silver,et al.  Decisional Guidance for Computer-Based Decision Support , 1991, MIS Q..

[39]  Burkhard Wünsche A Survey, Classification and Analysis of Perceptual Concepts and their Application for the Effective Visualisation of Complex Information , 2004, InVis.au.

[40]  Colin B. Ferguson,et al.  Cognitive style factors affecting database query performance , 2003, Int. J. Account. Inf. Syst..

[41]  Patrick R. Wheeler The Myers‐Briggs Type Indicator and Applications to Accounting Education and Research , 2001 .