With trials for the 2012 Olympic Games in London almost complete, as a diehard trackie, I can’t help but reflect on the amazing standards that athletes must meet or exceed in order to qualify for their respective events. For instance, the “A” standard for the men’s 100 meter event is 10.18 seconds – that’s faster than the time it would take for many of us to boot up our computers. The standard for women’s high jump is 1.95 meters or about 6 feet, 4.7 inches – so an “A” standard athlete could easily clear the height of a very tall person. Olympic hopefuls work diligently to meet (or exceed) these high standards. Likewise, in a quest for excellence, we in the business intelligence world should strive to improve the design of our BI dashboards – the ones that guide our daily decision-making. We should be reviewing their effectiveness at least yearly. To that end, we’ve compiled a simple checklist to guide your dashboards towards the “A” standard.
Whittle them down to only the most relevant and timely information. With all the excitement around big data and the need to analyze vast amounts of information in order to spot trends, it’s easy to be swept away in a deluge of data and be distracted from what really matters. As excited as you (or the users you serve) may be to display all kinds of new information, remember that some data is a distraction rather than relevant to the decision-making process. So be cautious of the information overload that can hinder the effectiveness of your dashboards. Each organization must determine what really matters to decision-makers (this will vary between them) and center dashboards around the metrics most relevant to each department.
Implement appropriate design. When it comes to dashboards, looks do matter. But dashboards aren’t just eye candy. They’ve become a standard point of reference for business managers and executives who need to monitor company operations – often at a glance – in order to make timely decisions. In a 2011 interview with Dashboard Insight, Stephen Few, author of bestselling books on dashboard design and data visualization best practices (and also inventor of the bullet graph), explains…
Back in September, we announced our BI Challenge 2012, a competition for students in Germany, Austria, and Switzerland to create innovative BI apps for a chance to win 5000 Euros. Last week, we held the awards ceremony in Düsseldorf and honored the 3 winners. They’ll present their apps to the larger public at our arc|planet user conference on October 30-31.
Three computing and economics students took home top prizes for applications they designed in the Innovation, Fast Mover and Business Excellence categories. From the many entries, the winners were selected by a professional jury of experts including Dr. Wolfgang Martin, one Europe’s leading analysts, Wolf Müller Scholz, publisher of Business Intelligence magazine, Hans Peter Wolff, CTO at arcplan, and representatives of Daimler AG and Wacker Chemie AG.
In the Innovation category, John Winkelmeyer from the Cologne University of Applied Sciences took 1st place with his application “Intranet Analysis Model – investigation into usage information for an intranet.” In the Fast Mover category, the winner was Iman Sheikholmolouki from the University of Technology in Munich with a mobile management information system for iPad that analyzes company data. It’s being used by arcplan’s customer Scout 24, one of the leading European groups of companies in the online marketplace. Daniel Horlbeck from the University of Applied Sciences, Berlin won the Business Excellence category. He developed an arcplan Enterprise 7 dashboard that supports the partner managers of Digital Wallet, a virtual organization that enables electronic financial transactions.
The BI Challenge’s goal is to allow tomorrow’s professionals and managers hands-on experience with arcplan’s flexible and innovative BI platform, arcplan Enterprise, during their studies. Examples of solutions that were submitted this year include management cockpits, web-based analysis and reporting applications, and Balanced Scorecards.
Congratulations to the winners! Interested in entering the competition? Details about next year’s BI Challenge 2013 will be released shortly at www.arcplan.com/de.
Companies that strive to grow and thrive rely on the insight gleaned from their business intelligence system. But when international growth is on the agenda, some businesses forget to prime their BI system for that change. At arcplan there are plenty of experts in this area since so many of our customers are multi-national companies, so we put together this list of items to prepare your international BI deployment for success. With Gartner’s 2012 global survey of CIOs revealing that business intelligence/analytics is their top-ranked technology priority this year, this list is more important than ever to guarantee that your BI system serves users worldwide.
1) Multi-Language Support
BI systems that will be used by employees in more than one country must be multilingual. While users in the U.S. see English or Spanish, users in Germany must have the option to display the system in German. Even better, the system should be able to identify a user’s language via the operating system settings and display their native language automatically. This first point is critical to the success of your system worldwide. If a business intelligence solution hinders useage due to something as simple as language support, it will never take off. Some configuration may be required, but this extra effort will always be worth it.
2) Multi-Currency Support
Any BI system deployed globally must be able to handle multiple currencies and should default to the users’ local currency. In Mexico, users should see all values displayed as pesos; in Canada, users should see values in Canadian dollars – always with the option to convert to U.S. dollars, euros, or any other currency the company uses. Paramount here is also the ability for the BI solution to display local decimal style, i.e. commas vs. periods. In the U.S., decimals are notated with periods (2.45), whereas most of Europe uses decimal commas (2,45). Your business intelligence should comply automatically.
3) Point-of-View Settings
Recently we have seen a dramatic change when it comes to deciding which screen size to design a new report or dashboard for. It’s always been a struggle for BI app designers to optimize applications to fit to the different sizes of desktop PCs and laptops, but adding mobile devices like smartphones and tablet PCs to the mix makes it even more complex.
The most natural solution of the past was to design two different views – one for the desktop and one for mobile deployment. But we no longer recommend this approach as the lines between different device categories are blurring.
Netbooks are encroaching on notebook and iPad territory, coming closer to their display capabilities. iPad has initiated a storm of new devices from other vendors with similar screen size. Even worse (from an app design point of view), Internet giant Amazon.com launched its Kindle Fire, whose screen size sits between traditional smartphones and tablet PCs. And now new devices like the Galaxy Note and the Galaxy III by Samsung, whose screen sizes are between the iPhone and the Kindle Fire, have found their own fans.
Although size does matter, screen size is not the sole point to consider when designing BI apps. There’s orientation to consider – which devices are optimized for portrait or landscape orientation – and on top of this, different vendors also offer a wide variety of pixel density – defined by pixels per Inch (PPI). For example, the new iPhone 4S with its Retina Display is able to display more pixels on its 3.5″ display than a decent netbook.
For app designers, it is impossible to create separate reports for every device, especially at organizations where BYOD (bring your own device) is the standard. This would end up being a total nightmare from a maintenance point of view. So what can we do? It’s time for a new and intelligent approach that will allow us to use one app and one report or dashboard layout for all devices.
We’ve been thinking a lot about the various ways organizations can improve their existing business intelligence applications. Many of arcplan’s customers have been with us 5-10 or more years and are continuously improving their BI along the way. Some of the initiatives we frequently hear about are related to data quality improvement, but this may be an anomaly. According to Ventana Research’s recent study, less than half of organizations surveyed have taken on some kind of information management initiative, like data quality or data integration improvements, in the last 2 years due to budget restrictions or lack of employees with the right skills.
I’d argue that data quality initiatives should be a “top 5″ priority for organizations in 2012. Why? Because of stories like this: A friend recently told me about a meeting at his company where the regional sales managers were giving their summaries of pipeline opportunities. During one of the updates, a director interjected that he didn’t see the favorable developments mentioned in Salesforce, their CRM system. Based on the information that was present in the system, the director figured that the quarter would be an average one. However, the updates from the sales manager would really swing the potential outcome of the quarter in a positive way. Now I bet that director had to make some decisions that were compromised by the (lack of) current information in the CRM system. He might have started strategizing about how to re-engage with the (assumed) stagnant prospects, started working with marketing on a nurturing campaign, asked the telesales team to reach out…any number of things could have happened based off of the faulty information available to him.
Unfortunately, many organizations have to contend with poor data quality which ultimately results in poor decision-making. After all, decisions are no better than the data on which they’re based. Reliable, relevant, and complete data (as opposed to the incomplete data set available to the director in my example above) supports organizational efficiency and is a cornerstone of sound decision-making. So what are some of the consequences of sub-par data quality?
1) Mistrust. Poor data quality often breeds mistrust among internal departments. I read a great example from 1998 (if you can believe it) that could have been written yesterday: