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To properly deliver on these promises, dashboards need to be visually effective. They don’t necessary have to look attractive, but need to be impactful and allow for interpretation without too much effort. In Stephen Few’s 2006 book, Information Dashboard Design, he stated that: “A dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance.”

Following on that premise we offer seven ways to make your dashboards as visually impactful and useful as possible.

1.     Key Performance Indicators (KPI)

Although we will focus this discussion on appearance, we can’t ignore what the dashboard needs to contain. The most important dashboard consideration is the message you are conveying. An attractive looking dashboard is useless unless it delivers valuable information and all required information fits on the dashboard. So dashboards need to be actionable and relevant to the intended audience. Delivering KPIs is critical, so the user can immediately determine how things are trending. And KPIs should be created with the corporate goals and objectives in mind.

KPIs can be defined as one of four types of metrics:

• Rates
• Averages
• Percentages
• Ratios

And they should all be shown trending over time. So, if the objective for the organization is to reduce costs by increasing customer self-service, then an effective KPI might be the ratio of online registrations to all registrations, month over month. That will give us an indication at how well the online registration system is working. Reporting systems don’t typically deliver these kinds of numbers, so you may have to do these calculations before plugging them into your dashboard.

2.     Allow for Interactivity

Playing, exploring, and experimenting with the charts is what keeps users engaged. Interactive dashboards enable your audiences to perform basic analytical tasks such as filtering the views, drilling down and examining underlying data – all with little training. Viewers need to be able to get the big picture from the dashboard that everyone sees and then be able to drill down into a view that tells them what they need to know to get their jobs done. Allowing your viewers to interact with dashboards lets them find hidden relationships in the data that you may never even have intended or thought of.

The Toronto 2011 Parking Infractions dashboard shown below contains several elements which are all joined together by street name, type of infraction, infraction time of day, and so on. As any part is interacted with, the entire dashboard is updated.

3.     Use Simple and Powerful Visual Elements

Sparklines are data-intense, design-simple, word-size graphics that provide a quick sense of historical context. When designing sparklines in reports, it is helpful to also highlight the minimum point and the maximum point.

Sparklines can also be used as thumbnails to indicate the necessity of drilling into the dashboard for further detail. That way you can hide the complexity of the numbers and show them only if requested.

4.     Don’t Cram and Jam

It’s easy to get overly ambitious and want to provide highly detailed, real-time dashboards covering each and every business challenge. But it is very bad practice to cram and jam too much into a single view.

Instead, produce dashboards that are tailored for specific audiences. Most systems will enable selectable areas to be part of a dashboard view based on user log-in credentials. If further detail is required, it can be accessed by drilling into that specific portion. This is a great use of sparklines.

Only include information relevant to your audience. That means customizing dashboards for unique people or groups. HR may find sales figures interesting but it’s just distracting if it’s not valuable to their job. It’s better to have less information on the dashboard and encourage the user to drill in to get more detail if required.

A dashboard should bring together common data elements from disparate sources such as customer information from CRM, email marketing and in-house sales order systems. If you are looking at a single customer view it only makes sense that it is all contained within one view!

5.     Location, Location, Location

Research shows that people read a dashboard the way they read a book. That means top left to bottom right. The visualizations which show the key metrics should be at the top and to the left of the dashboard.

Make sure that related visualizations where a comparison can be made are placed next to each other. The dashboard should be arranged to make the end user consume the dashboard in the order the dashboard creator intended it to be consumed.

6.     Make it Fit on One Page

Less is more. If it doesn’t fit on one page, it’s not a dashboard, it’s a report! Delivering the complete business snapshot on one page, providing that clarity has not been sacrificed, allows for faster data inspection and understanding. Don’t force users to scroll. Cognitive research – studies examining how the human brain processes information – has demonstrated that the ability to visualize all interrelated information sources together empowers people to more easily and clearly grasp the significance and overall meaning of an information set with greater accuracy.

7.     Colors, Sizes and Shapes

When designing your dashboard, embrace the use of colors, shapes, lines, thicknesses, degrees of shading, and other treatments that leverage visual perception. Things to avoid include overly cute widgets, 3D graphic treatments, and distracting color schemes.

Accountants have always known that visual pop-outs such as color can be used to highlight and draw attention to certain numbers. Negative values are set in red to quickly allow the viewer to find areas of concern. Similarly, the size of a circle can signify relative amount in sales or number of units sold,and the shading of that shape can inform another measure such as profit. Using a different shape is a great way to indicate another item or region. Humans are good at understanding values based on shape, colour, and size and less good at greys, texture and orientation.

Another great reason for using different shapes is that 12% of men and, therefore, 6% of the population is color blind. The most common color blindness is an inability to distinguish reds and greens.

Using different colors in the dashboard can draw attention to unique parts and using similar colors can tie two parts of a dashboard together. Generally, a complimentary color scheme can drastically improve the appeal of your dashboard as a coherent color scheme draws the whole dashboard together and makes it look more professional. A good starting point is to identify colors which are prominent in any image or visualization you have used on your dashboard and then use a color scheme to compliment these colors.

The two examples below both show the same data. However, it’s often difficult to gain insight and find patterns when looking at numbers in a Figure 1. Instead, when those values are combined in colored boxes, important information jumps out at the viewer as shown in Figure 2. In this case, size indicates sales volume and color shows profit.  And less space is used on your dashboard.

Figure 2Figure 1

8.     Some Don’ts

8.1        Avoid Pie Charts

Pie charts are generally considered poor data visualization for any data set with more than half a dozen elements.  A bar graph is a better alternative in this case. Pie charts are problematic as it is very difficult to discern proportional differences with a radially divided circle, except in the case of a small data set that has large value differences within it. Pie charts also pose a problem for labeling as they are either dependent on a color or pattern to describe the different data elements, or the labels need to be arranged around the perimeter of the pie, creating a visual distraction.

8.2        Avoid Unnecessary Color

In this example, having a different color for each column in the column graph is unnecessary and even distracts the user from the data.  Having just one color for all columns actually works better in this case.

8.3        Avoid Gauges

People seem to think that because cars and planes contain gauges, we must have them in business intelligence dashboards too.  Actually, they don’t provide many added benefits. Gauges show very little information and take up a lot of space. A bullet graph is much more effective in conveying the same information but in a much smaller space. Real estate is precious on a dashboard, and the space saved by using a bullet graph instead could be used for other information.

8.4        Avoid 3D

3D charts are best used in the scientific community for seeing patterns in n-dimensional data. Do not use 3D bar charts just for the sake of doing so or because you think they look cool. 3D charts can easily be misinterpreted and often distort 2D data. The best practice is to keep your charts simple.

9.     Conclusion

Visualization is often viewed as a personal preference. But it’s not. There are firm rules and best practices that will enhance the delivery of information. Follow them, and your dashboards will be useful and impactful.

Keeping track of money is one of the most fundamental skills we have today. We were taught how to count with building blocks as toddlers and how to quickly split the bill

when going on a double-date.

As (brilliantly) trained analysts we are expected to quickly calculate totals and estimate values. We do it every day and are pros at it. We take terabytes of data with millions of rows of complex numbers, and to help others understand it, we create beautiful Tableau dashboards to share with them. We already understand the data (because we are number experts!), and now it’s easy to share it so others do as well.

So estimating a barrel full of single dollar bills should be easy, right? But according to the guesses we had, apparently it’s not. Guesstimates ranged from $44 to $888.

Strategies for Success

There are a few strategies you could have used in calculating the number of bills in our barrel.

1) Guess. It’s just a game.

2) Count them. Don’t count each dollar, of course, but you could count the number of bills in a two or three inch vertical section and multiply that number times the number of similar sections in the container. This could yield a very good estimate.

3) Equate them. This strategy is best if you are “guessing” the number of bills in a known volume. In fact, it’s almost fool-proof in that situation.

The measurement of a dollar bill is 2.5 inches X 6 inches. The volume of one crumpled bill can be thought of as a cubic space taking up 2 inches X 1 inches (slightly thicker because it’s crumpled) X 5 inches (slightly shorter because it’s crumpled) which is 10 cubic inches per dollar bill.

The formula for calculating the volume of a cylinder is V=πr²h. The barrel we used measured 24 inches in height with a radius of 6 inches. And it was filled to about 18 inches. The Volume, therefore, is V= 3.14159 X  6² X 18 = 2035 cubic inches.

The calculated answer, therefore, is 203 since that’s how many 10 cubic inch bills it would take to fill that space. The right answer was in fact 201.

Who’s the smartest?

Who do you think correctly guessed calculated the dollar amount in our Cash Barrel!? Well, it wasn’t a highly paid data specialist attending the roadshow to see the latest features of Tableau. Instead, it was a woman from the catering staff at the Hyatt in Jersey City! Let’s call her Carmen (not her real name since I’m not sure the hotel would have allowed her to participate). Carmen nonchalantly said she was great with numbers and quickly and correctly answered the challenge! We sent her $201 which she enthusiastically accepted!

Thanks to everyone for participating. Check out the viz we created.

Business Users Have the Knowledge but Not the Proper BI Tools

End users are decision makers. However, all too often they don’t have the data necessary to make accurate, well informed decisions. Even though they understand the data that drives their business, they don’t have access to the tools to interrogate it. Think about it. The business tools we use every day don’t have the ability to generate insightful reports. If you are a sales manager, perhaps it would be good to know the percentage of client tasks sales people completed on-time and how that correlates to their performance, or simply how many tasks they have relative to sales performance -try extracting that from Salesforce! Perhaps you want to know how sales and marketing activities affect other channels of engagement such as the web. Unfortunately, the tools necessary for these queries are not easily within the grasp of most business users.

Instead, BI reporting tools and data warehouses are controlled by IT and rightly so. IT is the guardian of corporate data, but it’s not generally the function of IT to extract business insight from it. Therefore, solutions need to be available for users to interact with data without burdening IT when doing so.

Tableau Saves the Day – True story!

Last year, a middle manager at a major insurance company was asked to deliver a report to senior executives providing sophisticated sales analytics. He immediately engaged with the company’s Business Objects power user, but after two months of fighting with scripts, data incompatibilities and a general disinterest from IT about his reporting needs, the project had stalled. You would expect that after so much effort they could have completed the task, but it was no further along. Nothing tangible had been accomplished.

Since the manager was now behind on his deliverables, in desperation, he did an online search for something he could use himself. He stumbled across Tableau, installed it, and took a 30 minute online tutorial. He then connected to the corporate Oracle database, completed his analysis and created fantastic visualizations in less than three hours! That’s the power of placing analytics tools in the hands of the user.

This is a great example of how Tableau was able to bridge the technology gap between reports provided by IT and what is most useful for the business end user. Giving reporting tools to the business user, allows them to interact with data and ask iterative questions rather than looking at static reports that are not designed for their use.

By the Numbers

Let’s frame this discussion with some statistics:

• While most companies have BI systems in place, only 8% of employees are actually using BI tools (BARC).
• According to Gartner, 70 – 80% of BI projects fail.
• Cost and complexity account for 70% of the barriers to success (Gartner).

These stats exemplify what we are saying! Costly BI systems that are put in place are not accessible to end-users. Therefore, they provide little value and a lot of frustration.

According to an MIT study, only 4% of organizations use all the data they collect and 30% don’t use much of the data. 65% of organizations say they do not have access to the data they need to make key decisions. But even having access to the data is not enough. You also need the ability to interrogate the data to glean insight. A typical BI implementation takes 7 – 9 months (BARC). Most tools such as Tableau don’t normally take three hours, but time-to-value can be measured in days, not months. However, the biggest pay-off isn’t in time. It’s in the delivery of self-reliance and learning agility. You gain more insight and get much more work done.

Data Driven Rather Than Hunch-Based Decision Making

Stop guessing. Rather than basing decisions on a hunch, analyse the data your organization already collects to make superior, data based decisions. This will shift the question from, “What do you think” to “What do you know?”

By providing decision makers with tools that don’t require technical skill-sets and that can easily access information stored in corporate databases and spreadsheets, business users can gain new insights and perform their jobs more effectively.