Rescue time uses a reporting dashboard that allows its customers to analyze how they spend their time, and make appropriate adjustments.
Rescue time generates a reporting dashboard from collected data that analyzes “most productive days” and “least productive days”.
With the insights readers can adjust their daily and weekly agenda to match their performance, and hence they can make a more intelligent use of how they spend their time.
The site uses fragmentation in a good way by applying tabs to the reporting dashboard, hence separating averages, from the productive and unproductive days, and ultimately giving readers a focused view on the topic.
The reporting tabs have fully spelled out labels, and make use of the Von Restorff effect to draw attention to the unusual. This is achieved by applying highlighting that allows users to immediately latch onto the main keyword on a tab. For return users this formatting is a visual cue to not having to read the full label again at the second and any additional visit there after.
When switching tabs, the information is presented in a consistent way, allowing readers to quickly latch onto the information, and applying scanning patterns they recollect.
The color scheme and other means of formatting are kept as well consistent. It is chosen with consideration, limited to a maximum of four categories and systematically applied onto the design:
Red has an associated negative meaning and is used to spot distracting time. The other extreme is very productive time, which is indicated by blue.
These two colors show an opposite color contrast. All other categories that are between these two extremes take advantage of principles used with additive color mixing, i.e. the less productive the time category, the more red is contained in the category’s color, ultimately leading to a transition from blue to red, with purple in between.
A different color code is used for the work week indicating the most and least productive ways.
Each dashboard is structured in the same fashion:
The most important information, i.e. productive/non productive days is always located in the top left corner (with exception for the 60 day average). The information is interpreted and leaves no room for ambiguity. A helpful link is provided to explain the meaning of the metric should users feel they don’t understand.
Next to the week view, there is a doughnut chart, which extends the overview. The displays shows the distribution of hours and across all four categories. A summary in the doughnut’s center provides additional insights. When hovering over a segment of the dashboard, a tooltip provides information. The interaction is supported by increasing the size of a segment temporarily in order to make it clear which section users are working with.
Going to the right, secondary information is displayed in tabular form and in combination with bar charts, that carry over the meaning of color from previous displays. Although more detailed, the information is condensed to the top 7 activities and categories. Readers can drill down further into any of these by clicking on the label. Once clicked the user navigates away from the
Trending refers to the overall data which calculates averages and which is set since beginning a user collects data.
The bottom of the screen contains averages across the 3 top categories, and in the context of trending across a longer period of time.
Readers can choose to include weekends in the calculation of values.
What this dashboard falls short of is providing information as of how the averages are calculated. Are those derived from the beginning of time?
The content is organized and arranged in such a way that it can be viewed almost in its entirety on 13 devices.