Rethinking Business Intelligence Software

People don’t care about business intelligence software, they care about what it can do for them.  CAN is built on this idea.  Instead of focusing on business intelligence software, we are focused on providing answers directly to our clients.  We are improving this process by launching the CAN Portal.  The Portal is how we work with our clients.  It will allow you to get better answers faster and more securely.
What are your objectives?
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Dashboard Design: Bullet Graph vs. Bar Chart

We invest a lot of time and energy communicating our research, because unless we can effectively communicate our findings they are useless.  When the goal is to communicate the most valuable information with the least amount of ink that can be understood with the least amount of effort.  For your reference, our major influences are Deirdre McCloskey on writing, Stephen Few on dashboard design, and Edward Tufte on data visualization.

Recently, CAN conducted a customer satisfaction survey for the Georgia Regional transportation Authority.  In addition to developing, deploying and analyzing the customer survey, CAN went above and beyond to improve how GRTA reported the results of their annual survey.  In this post, I will explain why we used a modified bullet graph instead of a bar chart to answer the business question.

The purpose of the graph is to help answer the business question of how does GRTA compare to two competitors across 17 different metrics.  While GRTA needs to continually improve, for the purpose of  answering the business question the exact score was not important, but instead the difference between each competitor and compared to others how does GRTA score.  Comparing each company by metric was the main influence behind the design on CAN’s graph.

The Original Graph


 
 

The CAN Graph


– In the original graph, the bold vertical lines focus the viewer how each metric scored, by encouraging the eyes to go up and down.  In the CAN graph, the light gray horizontal lines encourage the eyes to travel left and right to compare each companies performance.  Also, we used light gray lines so that we did not dominate the graph with supporting data.
– In the original graph, there is no simple way to show the spread between the different competitors, besides comparing each line together.  However, it important to know how competitive each metric is when answering the business question.  When designing the CAN Graph, we darkened a length of the light gray horizontal lines to show the minimum and maximum score on the service quality index.  This
– In the original graph, using four different colors made it difficult to make a memorable distinction between each company, take up an unnecessary amount of space, and impossible for color blind (10% of males) to make distinctions.  Using different shades of gray CAN made it easy for everyone, including the colorblind, to distinguish between different companies.  In addition to adding an additional way to differentiate between companies, using different shapes allowed for better distinction when multiple companies score close to each other.
– In the original graph, the overall low graphical quality such as broken vertical lines, faded colors and pixilated font created an unnecessary distraction, and reduce the credibility of the results.  While this might seem petty, producing graphs that are crisp and well designed help develop trust with the audience.  In the CAN Graph, we produced the entire graph in black and white, so that the report can easily be reproduced on either a color or black and white printer.
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Dashboard Design: Teaching Strategic and Analytical Thinking

At CAN, we exist to provide our clients with leading edge methodologies that are both effective and easy to use.  This requires that we constantly learn about new tools and techniques, and hone a fine edge on the ones we keep to provide to our clients.

Previously on our blog, we have discussed the application of dashboards and aspects of dashboard design that facilitate rapid perception by the human brain.  How about using dashboards as a way to teach users a way of thinking?  In this blog, we will discuss using dashboards to promote strategic thinking through guided analysis.
One of our clients approached CAN with the following predicament.  Their enterprise operates nationwide with several districts responsible for operations within their unique geographic region.  Every year, the strategic planning division would produce a thick binder reviewing each districts market forecasts, opportunities, and past performance.  The intent was to assist the non-technical managers and business development of each district to think about trends in the market and industry to get more sales.  Although very well produced and full of useful information, these binders acted mostly as a reference and did little to encourage analysis by the end-user.
Our solution was to use the same information used to build the binders and create views using Tableau.  At first, these views replicated the familiar visualizations found in binders with an added level of interaction.  Then, we started to add new data sources into the existing information.  We connected industry forecasts, census data, economic indicators, past performance and connected all this functionality to a dashboard where the end user is able to bring in these factors at their command.  Populating the dashboard with the raw materials required for analysis, is the first stage.
The second stage is defining the business questions that the users need to answer to run their business.  We interviewed the executives on the strategic planning team and in several of the district offices to define what the most important business questions they needed to answer to run their business.  Instead of providing managers of each district with binders that pushed facts and figures at them, we created a work book of questions that needed to be answered and how the answers could be applied to running their district.
The third stage is doing most, not all, of the users’ work for them.  What I mean by this is producing dashboards that are 90% completed for the types of questions the user will want to answer.  Our goal is to support the user in asking questions and getting answers, not simply handing them the answers or making them build their own dashboards.  So, we build pre-made views for them.  For example, one aspect of our client’s business functions was closely related to population growth.  We produced a dashboard that integrated population growth figures for the past several years with our client’s historical sales figures and billable hours.  The district manager, interested in staffing requirements, can population changes across the region with his current staffing and identify where adjustments and hiring are likely to take place.
In designing guided analysis, the bottom line is producing dashboards that solve the business question that users need to answer.  This requires that the designers understand the purpose of each dashboard, how it will be used, and what the user intends to get out of it.  If your goal is to achieve data-driven decisions from non-technical managers, you must design so that the user is on the right track with the controls, but ultimately require their interaction and thinking to reach the outcome.
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Dashboard Design: Design for Parallel Processing

The value of dashboards and visualizations are that they allow users to shift from serial to parallel processing.  When reading a block of text you can only process the information serially by starting at the top left of the text and finishing the bottom right. Dashboards and data visualizations allow you to absorb information in parallel making it easier to absorb information quickly, identify relationships and trends.
Download our eBook, “Dashboards: Take a closer look at your data”.
However, the lack of serial processing requires that dashboards be effectively designed so that information can be absorbed as easily as possible.  This requires that dashboard be designed for pre-attentive processing or for “the unconscious accumulation of information from the environment” (Wikipedia).  Pre-attentive processing is specifically designed for parallel processing.  Pre-attentive processing allowed our ancestors to continually scan the horizon to identify opportunities and threats.  If well designed, a dashboard is modern-day equivalent of the horizon of the savanna, a data rich experience where it is easy to absorb the most important information, identify relationships and spot trends.
The basic principle of designing a pre-attentive dashboard that enables parallel processing is to keep element natural.  Replace bright bold colors with neutral and natural hues, and pie charts, gauges and traffic lights with hue, intensity, location, orientation, line length, line width, size, shape, added marks, enclosure, and motion.

Three Types of Dashboards

A dashboard is a single display that in a glance provides essential information for a specific objective. Since you are limited to a single display capable of being monitored at a glance, the first step of dashboard design is to select the purpose of your dashboard. This provides you with a filter to make sure that your dashboard effectively accomplishes its intended purpose.

Will it be strategic, analytical or operational? Answering this question will keep your dashboard from falling victim to trying to be everything to everyone.

Strategic dashboards provide managers and executives at all levels of the organization the information they need understand the health of the organization and help identify potential opportunities for expansion and improvement. Strategic dashboards do not provide all the detailed information needed to make complex decisions, but instead help executives identify opportunities for further analysis. A strategic dashboard should be simple and contain aggregate metrics the represent the over all health of the organization. Typically there is no need for interactive features and the data should be updated no more than monthly.

Analytical dashboards provide users with the data they need to understand trends and why certain things are happening by making comparisons across time and multiple variables. Analytical dashboards often contain more information per square inch than both strategic and operational dashboards. Since understanding is the goal analytical dashboards can be more complex than strategic or operations dashboards. Also, while analytical dashboards should facilitate interactions with the data, including viewing the data in increasing detail, it is important to maintain the ability to compare data across time and multiple variables. If you lose the ability to compare data then an analytical dashboards is no longer able to accomplish the goal of allowing users to understand trends and why things are happening.

Operational dashboards are used to monitor real time operations and alert the users to deviations for the norm. This often means that operational dashboards need to be updated frequently if not in real time, contain less information than analytical or strategic dashboards, and make it nearly impossible to avoid or misunderstand an alert when something deviates from the acceptable standards.  Operational dashboards should provide users with specific alerts and provide them with exactly what information they need to quickly get operations back to normal.

Download our eBook to find out more about using dashboards to get a better look at your data:

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