ACC 430 Module 3 Visualization and Dashboard Assignment Example

Six Tiles and No Pie Charts: Designing a Monthly Dashboard for a Distributor's CFO

[Student Name]

Southern New Hampshire University

ACC 430: Data Analytics for Financial Professionals

Module Three Assignment

[Instructor Name]

[Date]

The organization, setting and figures below are a composite written as a model document. No real employer, client, colleague or patient is described.

Six Tiles and No Pie Charts: Designing a Monthly Dashboard for a Distributor's CFO

Audience and Decisions

The CFO reviews results once a month, usually in the 30 minutes before the management meeting. In that meeting she decides three kinds of things: whether to adjust prices or push back on supplier increases, whether to tighten credit for slow-paying accounts and whether warehouse and delivery staffing match volume. The dashboard exists to support those decisions. Few (2013) treats a dashboard as a single screen that shows, at a glance, the few things a person most needs to watch, and that idea sets the constraints here: one page, a handful of measures, readable in minutes.

Measures

Table 1. Dashboard Measures

Each measure maps to a decision. Measures that do not, such as total orders processed or website visits, were excluded even though they are easy to calculate.

Chart Choices

Trends over 13 months, days sales outstanding and inventory turns, are line charts with the target drawn as a thin reference line, because lines make direction and change easy to see. Gross margin and cost to serve by segment are horizontal bar charts sorted from highest to lowest, because the reader needs to rank segments and compare their lengths, which people judge accurately. Revenue against plan and fill rate are bullet graphs, which show a single value against a target and ranges for poor, acceptable and good in a fraction of the space a gauge would need. There are no pie charts, because comparing slices requires judging angles, which people do poorly, and no three-dimensional effects, which distort values. Tufte (2001) argues for maximizing the share of ink that presents data, and these choices follow that principle.

Layout and Color

The page has three bands. Across the top, an exceptions strip lists any measure outside its tolerance, in plain words, for example "Restaurant segment gross margin 3.1 points below target." The middle band holds the four trend and comparison charts, and the bottom band holds the two bullet graphs. All charts use the same muted gray palette, with red reserved for values outside tolerance and a single blue for the current period. Using color only to signal means that when red appears, it means something. Labels sit directly on lines and bars rather than in a separate legend, which saves the eye a trip across the page.

Drill-Downs and Refresh

Each tile links to a detail view: segment margin drills to product categories and customers within the segment, days sales outstanding to an aging report by customer and cost to serve to route and order detail. The dashboard refreshes automatically from the cleaned data set early each month, once the books close, and the date of the data is printed in the corner. Richardson et al. (2021) emphasize that communicating insights includes making clear how current the data are and where they came from, so the reader can trust what she sees.

Accessibility and Consistency

Two smaller choices make the page usable in practice. About one man in twelve has some form of color vision deficiency, so red is never the only signal: values outside tolerance also carry a small marker and appear in the exceptions strip as text. And every chart that shows money uses the same units, thousands of dollars, with the same number of decimals, so the reader never has to check whether one chart is in thousands and another in millions. Axes on bar charts start at zero, because bars encode values by length and a truncated axis exaggerates differences; line charts of percentages use a narrower axis where small changes matter, with the range labeled clearly. These rules are written into a short style guide so that the next analyst who adds a chart follows them.

Questions the Dashboard Should Prompt

A good dashboard raises questions as well as answering them. When the restaurant segment's margin falls below target, the next question is whether price, product mix or cost to serve moved, and the drill-down is arranged in that order. When days sales outstanding rise, the CFO's next question is which customers are slow, so the aging view opens sorted by the largest balances past due. Designing these paths in advance means the dashboard leads the reader to the next decision rather than ending at a red tile.

What Was Left Out

The first draft had fourteen charts. Removed were total orders, revenue by warehouse, a map of customers, a word cloud of product names and several measures that duplicated others. Each was interesting, but none changed a decision the CFO makes monthly. Some moved to detail views; others were dropped.

Testing the Design

Before release, the CFO was shown the dashboard and asked three questions: which segment's margin needs attention this month, whether collections are improving and whether the company is on plan. She answered all three in under a minute. A fourth question, why restaurant margins fell, required one drill-down, which was the intended path. One change came from the test: she asked that prior-year values be added to the segment margin bars as thin markers, which was done before the first live release.

Conclusion

The dashboard presents six measures tied to the CFO's monthly decisions on one page, uses line charts for trends, sorted bars for rankings and bullet graphs for targets, places exceptions at the top and uses color only as a signal. Detail is one click away. The design was tested with its reader, and what it leaves out is as deliberate as what it shows.

References

Few, S. (2013). Information dashboard design: Displaying data for at-a-glance monitoring (2nd ed.). Analytics Press.

Richardson, V. J., Teeter, R. A., & Terrell, K. L. (2021). Data analytics for accounting (2nd ed.). McGraw Hill.

Tufte, E. R. (2001). The visual display of quantitative information (2nd ed.). Graphics Press.