Based on our knowledge and research into the problem domain, we can come up with initial follow-up questions after looking at the simple linear metaphor visualization:
- We started both of these initiatives right before a holiday weekend. How do we know that this uptick in sales is not just a seasonal trend?
- Total sales are up, but has the new store layout succeeded in improving the performance of some departments that were struggling before?
- Are we succeeding in getting more customers into the store and not just selling more to existing ones?
- Are customers shopping more departments and buying a more diverse mix of items?
Asking these kinds of questions is a great exercise to begin taking a visualization to the next level because they prompt us to add more dimensions that allow viewers to explore and understand the subject from additional angles and in more detail. There are a variety of solid techniques that can help achieve this additional dimensionality. Below are the answers to these questions:
5. Add small multiples. As described by author Edward Tufte, small repeated variations of a graphic side-by-side allow for quick visual comparison. Whenever possible, scales should be kept the same and the axis of comparison, aligned. Adding some small, stacked thumbnails of our chart next to the main one allows a comparison of sales trends for the same period last year, and the one before that. (See Figure 6, at left.) This answers our first question: sales do normally go up this time of year, but the increase seems to be quite a bit bigger this time, so it is probably not just the normal seasonal cycle.
6. Add layers. Adding extra levels of information, while preserving the high-level summary data, can make a graphic more flexible and useful. Next, we are going to break down the "top line" of total sales into departments. (See Figure 7, at left.)The resulting stacked area chart answers our second question, showing that sales from the appliances department have increased as a proportion of the whole, but media department sales have not improved much.
7. Add axes or coding patterns. Another way to get more dimensions in a graphic is to add additional patterns for coding information, such as varying the shape or color of points on a plot based on a variable. In some cases, an extra axis in space, alongside an existing one or in a new direction (for a 3D chart), can also be useful for showing new variables. It's important to be careful with this approach, as it can add clutter, but when used sparingly and with good design principles it can increase a graphic's usefulness. In Figure 8 (at left) we added an additional vertical axis on the right to show daily foot traffic into the store, with its scale overlaid carefully to be comparable but distinct. To answer question number three, “Yes; we have increased foot traffic, but only after the sales promotion.”
8. Combine metaphors. So far, we have used a linear metaphor for our visualization. However, to answer our last question, we want to add a network metaphor to show connections between product categories in purchases. A pair of circular relationship (chord) diagrams showing snapshots at the beginning and end of the time period under consideration can help compare these connections. Like a pie chart, each product category is assigned a section of the circle, by percentage of total sales, but the center of the circle is hollow. If a majority of purchases containing items in one category also included items in a second category, a line is drawn to that second category; line width is based on the average proportion of both categories in the mixed purchases. As shown in Figure 9 (at left), the increase in these chord lines from the first to second diagram suggests there are indeed more purchases that cross departments since our initiatives went into place.
This relationship data would be even better if we could see it at any chosen point in time (for example, to see what effect, if any, the layout change alone had, before the promotion started). A zoomed-in view of the chord diagrams for detailed study might be useful, too. Clearly, some presentation media lend themselves to these opportunities more than others. As our graphics increase in complexity and sophistication, we need to think more carefully about how to deliver them.
Consider New (and Old) Delivery Methods
The point of any visualization is to be viewed by the right people, in the right context. Unfortunately, many business visualizations have a fleeting life on a slide, up one minute on a low-resolution projector to be scanned from across the room, and nothing but a vague memory the next.
What if, instead of a “flash on a slide” with all of these limitations, Joe's final visualization was printed in high-resolution color on a handout? Everyone could refer back to it as a touchstone during the whole presentation, seeing how the data backs up Joe's conclusions. Afterward, they could tack it up on a whiteboard for further study and follow-up.
On the other hand, maybe Joe needs people at a remote site to see this graphic or he would just prefer not to kill so many trees. He might consider putting a high-resolution version on the Web (or corporate intranet) for viewing on a PC or tablet. This could be as simple as a static graphic like the paper copy, but it also opens all kinds of possibilities for interactivity. To give just a few examples, we could enable scrubbing through time (great for seeing more network metaphors), drilling down and zooming out for a bird's eye view, seeing new data live as it becomes available or even manipulating future variables to watch different scenarios play out.
The chart in step 5 is particularly exceptional, but then the visuals fall apart once he adds area charts. Area chart (and stacked bars) do a poor job at preserving true proportions for all sections except the bottom color and the total.
Overall though, this is a great way to think through visualization design if you don't know where to start.