When I talk to audiences about performance dashboards, I'm invariably asked how to get executives and analysts to abandon eye-bending spreadsheets packed with hundreds of data points per page in favor of more visual displays populated with charts and graphics.

This is a complex question because the answer involves sorting out and addressing two intertwined issues: 1) people's inherent resistance to change and 2) the quality of the visual design. In the end, users will adopt a visual display of quantitative information if it adds informational value, not because of its visual appeal.

Change Management

No Surprises. As I argued in a recent blog on change management, change disrupts people's rhythm and makes them less productive in the short run. Some will become anxious and lash out against the change even when it is in their long-term best interests.

Any time you change the way you present data to users, you force them to work harder--at least in the short term. They need to spend additional time learning the new layout, double checking numbers, experimenting with new functions and filters, and so on. Most people resist this short-term hit to their productivity. To avoid a mutiny, you need to prepare users for the change way ahead of time. If they know what's coming, they can budget their time and resources accordingly. No one likes a surprise!

Classes of Users. You also need to understand the classes of business users affected by the change and how each might react. Executives will react differently than managers who will react differently than analysts and operational workers. You need to develop a change management strategy that addresses the concerns and issues of each group and provides the appropriate levels of training and support.

For example, there will always be a small group of users who will resist change at all costs. These folks need high-touch training and support. That means offering one-on-one training (especially if they are executives). It also means duplicating the old environment inside the new one. If they are used to viewing spreadsheets, you need to show them how to use the new system to export a spreadsheet to their desktop that contains the same data and layouts as the old environment. Gradually, you can wean them off the older views by showing them how the new environment can make them more productive. But this takes a lot of patience and hand-holding.

Prototyping. It's also important to manage expectations and get users to buy into the new environment. The best way to do that is to solicit user feedback on an initial prototype. For example, at 1-800 Contacts, an online provider of contact lenses that I profiled in the second edition of my book, Performance Dashboards: Measuring, Monitoring, and Managing Your Business, the BI team built an executive dashboard to monitor sales and orders every 15 minutes. It discovered that some executives preferred to see data as line charts, while others wanted gauges and others preferred tables. So the team displayed all three graph types on the one-page dashboard to address every executive's visual preferences. This simple dashboard is very effective in helping executives keep their fingers on the pulse of the business.

Be careful during prototyping not to abdicate responsibility for the design of the environment. While it's important to get user feedback, it's critical that you let designers skilled in the visual display of quantitative data establish the look and feel of the dashboard--the fonts, colors, layouts, and navigational cues. Once you've established the framework, then ask users to comment on the value of data and metrics displayed, the navigational flow of the environment, and its ease of use.

Visual Design Techniques

The second major impediment to adoption is that many visual displays of quantitative information are suboptimally designed. The displays make it harder, not easier, for users to glean the meaning of depicted data. Users must spend more time examining the visual display to spot problems, trends, and outliers and make relevant comparisons.

Stephen Few, a renowned visualization expert, cites many visual design faux pas in his books and articles. These range from the overuse of color to 3-D chart types and poorly labeled graphs. His maxim, "Make every pixel count" is a wise one. One key issue that is often overlooked, however, is the need to tailor and evolve the density of visual displays.

Sparsity versus Density. Sparse displays contain fewer information objects than dense visual displays. As a result, sparse displays are easier to use because users can absorb relevant information quickly. However, sparse displays risk containing too little information. If users have to click several times to view information that they could previously view on a single page, they will get frustrated and stop using the tool.

On the other hand, dense displays can overwhelm or intimidate users with too much information at once. Users may feel reluctant to learn the new environment and revert to prior methods of consuming information.

When deciding how many objects to put on a single screen, it's important to remember that each class of users (and individuals within each class) will fall on a different point in the sparsity-to-density spectrum. Tailoring displays to these preferences can significantly aid adoption. It's also important to recognize that user preferences change over time. A simple, sparse screen may suffice when users first begin using a new display, but as they become more familiar with the layout, the data, and functionality of the new environment, they will demand denser displays. As a result, you will need to continuously evolve your visual displays to keep pace with the visual IQ of your users.

Summary

The bottom line: users want information and answers, not pretty pictures. They will reject graphical displays that obscure the meaning of the data and make them work harder no matter how visually appealing the interface. Conversely, they will overcome their natural resistance to change and adopt visual tools that make it easier to spot trends, problems, and outliers than existing methods.

If you focus on the data, not the pictures, and manage change wisely, you will succeed in converting your users to new visual methods for viewing quantitative information.