COIS13013 - Performance Dashboard Critique for Business Intelligence

This report provides an analysis and critique of a business performance dashboard, focusing on its design and effectiveness in illustrating key performance indicators. The dashboard's visual objects, including bar, column, and line charts, are evaluated for their ability to convey quantitative and qualitative measures related to new accounts, member service activity, and traffic sources. The critique highlights shortcomings such as limited space for reflection, unclear data representation, and poorly organized data groupings. The report suggests improvements, such as incorporating metrics, reports, and multi-page documents to provide explanatory narratives and ensuring visualizations accurately represent the information required. The analysis references external sources to support the evaluation of the dashboard's design and its alignment with best practices in information presentation.

BUSINESS INTELLIGENCE
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Table of Contents
Performance Dashboard...................................................................................................................2
Critique of the dashboard design.....................................................................................................3
References........................................................................................................................................4
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1.0 Performance Dashboard
Performance dashboards describe the company's strategy regarding the initiatives, metrics,
objectives, and tasks customized for specific groups. The performance management system
gauges the organization's achievement of its goals; and reports the current financial status on one
page. The business performance features from the bar, column charts and single line curves
showing the percentages. According to Yigitbasioglu and Velcu (2012), the visual representation
helps to identify the company's patterns, outliers, trends, correlations and business conditions.
Essential characteristics of the dashboard include the interactivity aspect; that is, the use of drill-
down and filtering to show underperforming programs (Yigitbasioglu and Velcu, 2012, p. 50).
Also, they show all performance measures to be evaluated.
Information provided in the dashboard includes percentages of new accounts between April 2016
and April 2017; total accounts; member service adoption during the same period; member
services activity; traffic source; browser types; and device usage. The new accounts chart shows
the number of new profiles between the mentioned period, while the visits to member services is
a single line chart showing the trend of member visits between April 2016 and April 2017
(myGov, 2017). The member service adoption chart shows percentages of people subscribing to
the services including 1,2,3, 5+ and 4. Notably, the member's activity bar chart identifies the
rates of members engaging in Medicare, Centre link, Child support, ATO among other services
over the course of one year. Similarly, the linked member service identifies percentages of
people engaging in the activities mentioned above.
Visual objects utilised in this dashboard are bar, column and line charts (KeenOI, 2012). The
objects display data on the organisation's performance with emphasis on new accounts, total
accounts and member services activity. One of the bar charts is the traffic source which explains
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percentages of people visiting Google, Direct, ato.gov.au, humanservices.gov.au and other
platforms. Qualitative measures identify the amount while qualitative approaches examine the
quality of particular processes or practices (Weiss et al., 2018, par. 4). In this case, the new and
total accounts are quantitative measures; while the browser types and device usage represent
qualitative approaches – this is because they show the members preferences. For instance, data
usage evaluates the percentage of people using mobile, desktop and other techniques to access
myGov.
2.0 Critique of the dashboard design
Stephen Lew explains that dashboards display data about the company’s objectives and
consolidates this information within one screen (Torabi et al., 2015, p. 320). The technique
utilises visual objects such as charts, and graphs to explain the dashboards indicators.
Appropriate designs of dashboards allow an individual to track the performance of projects and
programs implemented. One demerit of the model is that it does not provide enough space for
reflection or critical analysis of the data. To mitigate this dashboard can utilise metrics, a report,
and a multi-page document - this provides an explanatory narrative about the data presented.
Notably, poor dashboard designs fail to convey vital data and make the information less
authentic.
The charts in this design do not express the meaning of data. According to Buttigieg (2017),
visualizations must represent the information a person requires. For instance, each dashboard
should indicate specific goals, limitations, and requirements – this helps address frequent
business questions (Buttigieg, 2017, p. 402). Another demerit of the dashboard design is the
visual images used. The bar charts, column charts, and line graphs do not represent two or more
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variables. Also, the range is fixed; with the grouping of values within data poorly organized. An
example is the device usage and visits to member services charts.
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References
Buttigieg, S. 2017. Hospital performance dashboards: a literature review. Journal of Health
Organization and Management, 31 (3), 385-406.
Keena. 2012. Keen OI. Retrieved June 2, 2018, from Dashboards by Keen IO:
http://keen.github.io/dashboards/
myGov. 2017, May 15. GOV.AU Performance Dashboard. Retrieved June 2, 2018, from
myGov: https://dashboard.gov.au/dashboards/1-mygov
Torabi, M. et al. 2015. Development of Performance Dashboards in Healthcare Sector: Key
Practical Issues. Journal of the Society for Medical Informatics in Bosnia & Herzegovina,
23 (5), 317-321.
Velcu, O. Y. 2012. A review of dashboards in performance management: Implications for design
and research. International Journal of Accounting Information Systems, 13 (1), 41-59.
Weiss, D. et al. 2018. Effect of a population-level performance dashboard intervention on
maternal-newborn outcomes: an interrupted time series study. BMJ Journals, par. 4.
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