Database Reference
In-Depth Information
should have an interface that quickly guides decision makers to the answers
they seek, telling if the indicator is on track.
Operational dashboards
are designed to monitor the company opera-
tions. Monitoring operations requires more timely data, tracking constantly
changing activities that could require immediate attention. Operational
dashboards require a simple view to enable rapid visual identification of
measures that are going away from the goals and require immediate action.
Thus, the design of these kinds of dashboards must be very simple to avoid
mistakes. The timeliness of operational data can vary. If things are on track,
periodic snapshots may be sucient. However, if a measure deviates from the
goal, operational managers may want real-time data to see if the variance is
an anomaly or a trend.
Analytical dashboards
support interaction with the data, such as
drilling down into the underlying details, to enable the exploration needed
to make sense of it, which means not just to see what is going on but to
examine the causes. Therefore, analytical dashboards must support what we
called exploratory data analysis in Sect.
9.1
.
9.3.2 Guidelines for Dashboard Design
In order to design a dashboard that complies with the needs of the
intended audience, the visual elements and interactions must be carefully
chosen. Factors such as placement, attention, cognitive load, and interactivity
contribute greatly to the effectiveness of a dashboard.
A dashboard is meant to be viewed at a glance, so once the elements to
be shown have been selected, they must be arranged in a display that can be
viewed all at once in a screen, without having to scroll or navigate through
multiple pages, minimizing the effort of viewing information. In addition,
important information must be noticed quickly. From a designer's point of
view, it is crucial to know who will be the users of the dashboard we are
designing and what their goals are, in order to define to which of the above
categories we defined the dashboard belongs. This information is typically
obtained through user interviews.
To design a dashboard that can be effective and usable for its audience,
we need to choose data visualizations that convey the information clearly, are
easy to interpret, avoid excessive use of space, and are attractive and legible.
For example, dashboards may provide the user with visualizations that
allow data comparison. Line graphs, bar charts, and bullet bars are effective
visual metaphors to use for quick comparisons. Analytical dashboards should
provide interactivity, such as filtering or drill-down exploration. A scatterplot
can provide more detail behind comparisons by showing patterns created by
individual data points.
Search WWH ::
Custom Search