Best Practices are the guidelines for building digital dashboards that we believe result in a useful dashboard. While you can design a digital dashboard however you wish, the following practices result in a much more useful, efficient, and aesthetically pleasing dashboard. These practices are also extremely useful when starting the design process of a dashboard project.

Target User

The first and most important practice of building a dashboard is identifying who your target user is. A dashboard aimed at an executive of a company and one aimed at the marketing director are going to be very different. During the entire development process the end user should be kept in mind and the application tailored to this user. The tailoring process may include simple things such as placement of controls or data sources, but it can also include more complicated things such as the flow of the entire dashboard, or viewing secure data through a secure connection.

Right tool for the right job

A difficult requirement of building a digital dashboard is to decide what type of data visualization to use for different kinds of data. Generally, data should be displayed as follows:

·         Geographical data (i.e. Sales by Province in Canada) – Map

·         Data over time, ratio data, comparison of linear data – Chart

·         Snapshot data, single values (i.e. KPIs) – Gauge

·         Multidimensional data - OLAP

·         Other data – Diagram

Using this list should make it easy to break down any data into a group and display it with the appropriate data visualization tool. Further to this, making a dashboard dynamic so that the user is free to change the data visualization on demand is also a good practice, as there may be a perspective the user wishes to view that cannot be predicted while developing. Often times there are ways to get dynamic controls without having to code yourself, an example being Dundas Chart for OLAP Services which has a lot of end-user manipulation controls already built-in to the control.

Correctly Identifying KPIs (Key Performance Indicator)

A KPI, or Key Performance Indicator, is a quantifiable measurement that reflects the factors which contribute to success within a company. Usually different people within the company or third party consultants agree upon these measurements beforehand, but sometimes these are defined by the dashboard developer. It is imperative that KPIs be chosen correctly, if they are not it can amount to incorrect data leading to bad decisions. Research and time should be devoted to learning the organization or group’s important indicators of success as this could make or break a dashboard.

Context

Context is an item which in most dashboards is completely forgotten. This is baffling, as without context, KPIs are completely useless. Consider the following two items of data:

Figure 7: Example data with no context

After a quick glance at Figure 7, the following assumptions are made: Nick is doing really well in sales and everyone else is not, and the revenue per sale is pretty high. This, however, may not be the case.

Figure 8: Same data as Figure 7 with context

Figure 8 shows the same data with context. In this case, it is clear from the chart that no employee has hit the sales target this month. As well, it can now be observed from the gauge that the revenue per sale is not within the expected range. Ideally the gauge should be further improved by an explanation as to what the range and marker are, but at the very least marking the gauge gives it sufficient context.

While giving context to data may seem like an obvious step, it is the most omitted practice by developers of dashboards. In most cases, context is left out because the person creating the dashboard has been working with the data so much they know what “good” and “bad” data is. This assumption, however, cannot be applied to the end user as they may draw false conclusions.

Visual Aesthetic

Visual aesthetics include animation, palettes, 2D and 3D effects, and the general look and feel of the actual controls. This is closely related to the layout of a dashboard but is concerned with the aesthetic appeal of specific items within a dashboard rather than the overall design. While visual aesthetics are important in making a dashboard attractive, developers must be careful that the visuals do not interfere with the usability and efficiency of the digital dashboard.

Customizability

While great care should be taken in deciding what data is important for the user of a dashboard to see, providing some ability to customize the view is a good practice to follow. This point is especially true in OLAP driven digital dashboards where the data is multidimensional and the only way to formulate a coherent picture of the data is to view it from all angles. As well, giving the user the ability to change their perspective of the data often allows them to see trends or important changes within it that the user may not have been able to see otherwise. Reporting Services is an excellent example of a tool that is devoted to giving the user the ability to modify the underlying data query with little effort, and as such has enjoyed great success in the enterprise market.